What loss function is appropriate for finding "points of interest" in a array of x,y inputs
You don't have to use machine learning to solve the problem.


Unify the scale of each data input (or each curve), such as normalize to $[0,1]$ (not necessary).
Calculate the slope of each pair of points $\frac{(y2 - y1)}{(x2 - x1)}$.
Set the threshold. Compare the difference between two adjacent slopes, the difference exceeds the threshold are marked as POI.


Isn't that simpler?

If you must solve the problem with CNN, what I can think of is that you first collect (or draw) a bunch of curves, mark the POI in advance, and then feed it to the CNN model.